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Stratospheric Balloon Landing Suitability Analysis in Arizona, USA
No full textStratospheric balloons are increasingly important platforms for atmospheric research, remote sensing, and testing space-bound technologies. A critical operational challenge for high-altitude balloon operators is rapidly identifying safe and viable landing zones, especially in emergencies. This study aims to (1) quantify which geographic, demographic, and regulatory factors should most affect landing zone suitability across Arizona, and (2) produce a decision-support map to enable high-altitude balloon operators to quickly select safe landing areas. To achieve this, the study utilizes the Analytical Hierarchy Process (AHP) to assign weights to multiple criteria – including population density, controlled airspace, powerline proximity, and Gap Analysis Project (GAP) Status Codes – based on expert/operator judgements. The study then applies these weights to spatial data within a GIS framework to generate a high-resolution suitability map, classifying areas from “highly suitable” to “not suitable.” The resulting output provides a tool that operators can reference in real time to reduce decision-making time and enhance public safety.This item is part of the MS-GIST Master's Reports collection. For more information about items in this collection, please contact the UA Campus Repository at [email protected]
Biological Insecticide Options for Bagrada Bug Management
No full textThis article in the VegIPM Newsletter (Vol. 16, No. 25) summarizes biological insecticide performance for managing Bagrada bug in organic broccoli. M-Pede and the M-Pede + Entrust tank mix provided the strongest suppression (≈60%), while Captiva Prime and Neemix reduced populations by nearly 50%. Products like Aza-Direct, Entrust, and Botanigard delivered more moderate reductions (≈30%), with none offering rapid knockdown. Results highlight the limited but promising tools available for organic growers seeking selective options for Bagrada bug control.Documents in the Arizona Pest Management Center collection are made available by the Arizona Pest Management Center (APMC) and the University Libraries at the University of Arizona. For more information about items in this collection, please contact https://acis.cals.arizona.edu/about-us/arizona-pest-management-center
Design and Optimization of Functional Polymer-Modified Liposome Formulations for Enhanced Delivery of Therapeutics for Cancer and Depression
Get PDFLiposomal drug delivery systems have established themselves as a versatile strategy for enhancing the therapeutic efficacy of both anticancer agents and central nervous system (CNS) therapeutics. These systems facilitate improved encapsulation efficiency, regulated drug release kinetics, prolonged circulation time, and surface functionalization for targeted delivery. The work performed in this dissertation encompasses a series of formulation and characterization studies aimed at optimizing liposomal systems for hydrophilic chemotherapeutics—specifically pemetrexed (PMX), 5-fluorouracil (5FU), and doxorubicin (DOX)—as well as the antidepressants paroxetine and venlafaxine. For PMX, a multi-targeted antifolate characterized by rapid systemic clearance and associated dose-limiting toxicities, the effects of incorporating polyethylene glycol (PEG) into the liposomal aqueous core were explored to modulate drug release. Formulations incorporating polyethylene glycol internally in the liposomes displayed a concentration-dependent extension of PMX release, with statistically significant differences observed at late release time points. This finding indicates that the manipulation of the internal liposomal environment can effectively fine-tune drug diffusion release kinetics. Similarly, polyethyleneimine (PEI), a cationic polymer known for its strong electrostatic binding capabilities and pH-buffering properties, was integrated in the aqueous core of liposomes to investigate its effect on encapsulation efficiency and retention of chemotherapeutic agents. This modification significantly improved drug loading and ensured sustained release for PMX, 5FU, and DOX, suggesting the broad applicability of PEI-based systems across a range of hydrophilic pharmacological agents. Moreover, studies examining ionic strength revealed that an increase in NaCl concentration resulted in decreased liposome particle size, likely due to enhanced lipid packing, while maintaining PMX encapsulation efficiency. Nonetheless, elevated ionic strength correlated with accelerated PMX release, possibly due to alterations in bilayer permeability and stability, emphasizing the critical need for precise control over formulation parameters to achieve desired release profiles. When extending these methodologies towards CNS therapeutics, liposomal formulations were developed both with and without PEI for encapsulating paroxetine and venlafaxine, two antidepressants of clinical significance. The inclusion of PEI markedly enhanced encapsulation efficiency and resulted in more sustained release characteristics, thereby addressing challenges related to low bioavailability and limited penetration across the blood-brain barrier. Surface modification studies were conducted on amine-bearing cationic liposomes, specifically those formulated with dimyristoyl phosphatidylethanolamine (DMPE), to explore rapid and scalable functionalization using PEG and the chelating agent dipicolylamine (DPA). The results indicated that PEGylation led to a 44% reduction in surface-accessible amines, while DPA modification resulted in a 28% reduction. These findings underscore the potential for controlled modulation of surface chemistry, making strides toward the creation of stealth nanocarriers with targeted ligand-mediated capabilities. In vitro cytotoxicity evaluations were carried out with PMX. They involved a lactate dehydrogenase (LDH) release assay against 4T1 breast cancer cells to determine the cytotoxic effects of PMX-loaded liposomes in comparison to free drug and blank liposome controls. Statistical analysis using one-way and two-way ANOVA revealed that liposomal PMX exhibited significantly greater and more sustained cytotoxicity over 72 hours, in contrast to the diminishing cytotoxicity of free PMX by that time. These findings suggest that encapsulation within liposomes can extend PMX activity, thereby decreasing dosing frequency while preserving therapeutic efficacy. This work demonstrates the capacity to meticulously engineer both the intraliposomal environment (via PEG or PEI incorporation) and external formulation conditions (ionic strength, surface modification) to optimize liposomal physicochemical properties and drug release characteristics. These strategies have been effectively applied to various drug classes, including antifolate chemotherapeutics, anthracyclines, antimetabolites, and CNS-active antidepressants. The integration of formulation optimization, surface engineering, and in vitro performance evaluation establishes a robust framework for the rational design of nanocarriers, addressing critical challenges in drug delivery to enhance therapeutic outcomes and expand the clinical applicability of liposomal systems in oncology and neuropsychiatric disorders
Germination and Seedling Development
No full textThis article, published in the Vegetable IPM Newsletter (Vol. 16, No. 21), explains how temperature, moisture, and soil conditions affect seed germination and seedling development, with focus on lettuce thermodormancy and managing heat with sprinkler irrigation.Documents in the Arizona Pest Management Center collection are made available by the Arizona Pest Management Center (APMC) and the University Libraries at the University of Arizona. For more information about items in this collection, please contact https://acis.cals.arizona.edu/about-us/arizona-pest-management-center
Effect of Melt-Domain Size on the Stability of Vapor Films: Implications for Explosive Submarine Volcanic Eruptions
No full textThe explosivity of eruptions in the presence of external water is determined by its thermodynamic interactions with magma. Critical parameters governing an energetic magma-water interaction include the duration of water boiling regimes and the associated rate of heat transfer from magma to the water. A range of melt fragments from micron to cm-size are commonly observed during such interactions. Therefore, the melt domain- or fragment-sizes, at a given melt-water mass ratio, likely provide a first-order control on the efficiency of magma-water interactions but has remained poorly constrained. Comparing high-temperature experimental results with milimeter-scale melt domains to the existing studies with centimeter-size domains, this study provides insights into the effect of fragment size on water boiling regimes. Spherical samples of re-melted mafic rocks with an initial temperature of ~1388 K (1115 ºC) were submerged in water. The temperature of the water was varied in the range of 276-365 K (3-92 ºC) between experiments but was kept constant during any given experiment. The experimental videos were captured using high-speed cameras from where the time scales of water boiling regimes were determined. Our experimental results show that mm-scale melt fragments are associated with shorter vapor film timescales compared to cm-sizes, where this difference increases with increasing water temperature. Using the stable vapor film time scales from the experiments and heat transfer modeling, the Leidenfrost temperatures were estimated. The time scales of stable vapor films provide constraints on the time available for mixing between melt and water along with any external trigger that may be required for energetic melt-water interactions and explosive submarine volcanic eruptions.Release after 11/13/202
Improving Zero-shot Relation Extraction via Rule-based and Prompt-based Methods
No full textRelation extraction (RE) is a foundational task in information extraction that aims to identify semantic relations between entities from unstructured text. While supervised relation extraction models have considerably advanced the state-of-the-art, they often perform poorly in low-resource settings. Zero-shot RE is vital when annotations are not available either due to costs or time constraints. As a result, zero-shot RE has garnered interest in the research community. In this dissertation, we propose rule-based and prompt-based methods to advance zero-shot RE. First, we introduce a new rule learning method that given a seed rule, learns many rules with a synonymous meaning. Rule-based approaches have the advantage of interpretability. Furthermore, the interpretability provided by rules is actionable. On the other hand, rule-based approaches lack the generalization power of deep learning systems. In this work, we aim to marry the advantages of the two directions. To that end, we propose an extension to Harris (1954)’s distributional hypothesis for rules. In particular, we propose to measure the similarity between pairs of slots (i.e., the set of concepts matched by a rule) using contextualized embeddings instead of lexical overlap. Empirical results demonstrate that this new similarity method yields a better implementation of the distributional hypothesis. Next, we develop a zero-shot RE method that formulates RE as a textual entailment task. Our method automatically generates templates using our extension of the distributional hypothesis to rules. These templates verbalize relation types, and are fed as hypotheses to an off-the-shelf entailment engine for classification. Our method achieves state-of-the-art performance for zero-shot TACRED, a popular RE benchmark. Finally, we introduce an effective prompt-based method for RE. With the arrival of large language models, many approaches have been proposed for RE, but they are often ineffective or require an accompanying masked language model or complex post-prompt processing. In this work, we propose a high-performing prompt-based method for RE that does not require any additional resources. Our experiments on four main RE datasets showed that our method outperforms previous state-of-the-art by a large margin.Release after 12/15/202
Multi-Dimensional Analyses into Plant Processing and Technological Changes during the Paleolithic-Neolithic Transition in North China
No full textThis project examines economic and technological specialization associated with the adoption of agriculture in North China between 26,000 and 8,000 years ago. The origins and spread of agriculture represent one of the most significant economic transitions in human history. It is widely believed that agricultural economies led to increased economic specialization and division of labor, two central aspects of modern economies. This specialization is thought to be reflected in technology, particularly in the development of specialized tools for processing agricultural products such as grains. In China, early farmers adopted ground-edged tools while continuing to use flaked tools and grinding stones, technologies inherited from their hunter-gatherer ancestors. This dissertation investigates whether economic and technological specialization was an inevitable outcome of plant processing or whether it occurred only in certain contexts. To address this question, I examine how a range of stone tools were actually used before and after the adoption of agriculture.The data for this study come from the Peiligang site in the Middle Yellow River Basin of North China. This region is particularly well suited for such a study because it was a center of early mixed millet and rice agriculture and contains cultural components spanning from the Upper Paleolithic to the Early Neolithic, with both pre-agricultural and agricultural practices represented within the same locality. Artifact functions were investigated using two independent lines of evidence. The first is use-wear analysis, which examines physical alterations on tool surfaces to infer motions of use and contact materials, such as soft plants, wood, animal tissue, hide, and bone. The second is microfossil residue analysis, including starch grains, phytoliths, and microfibers, which provide direct evidence of the plants that people were cutting, grinding, and scraping with these tools. By integrating experimental models with archaeological evidence, I propose a new interpretation of the persistence of flaked tools alongside innovations in ground stone technology. Specifically, my experiments suggest that compared to flaked tools, ground-edged stone tools do not show significantly increased efficiency in harvesting grasses, but that they are more efficient for harvesting fibrous plants and weeds. Supported by correlations from archaeological analyses, I argue that ground-edged stone tools were developed in response to the long-term and large-scale demands of bast fiber processing in the Early Neolithic. Although they were also commonly used for harvesting and processing plant foods, these functions were shared with flaked tools. Grinding stones, by contrast, show a trajectory of intensification rather than replacement, with larger and more complex forms supporting sustained processing of cereals and other plants. Residues preserved in pottery vessels further demonstrate the diversification of plant use, including alcohol production and ritualized consumption. Together, these lines of evidence reveal that toolkits became increasingly specialized not through simple substitution of old technologies with new ones, but through overlapping and complementary roles in food and non-food plant processing. This dissertation therefore offers new insights into the dynamics of technological continuity and innovation within broader social, cultural, and environmental contexts.Release after 01/01/203
Computational Methods for Biomedical Data
No full textBiomedical data provides a rich opportunity for the development of new statistical and deep learning tools. In this work we focus on two problems in biomedical data analysis, namely classification of effusion
synovitis in knee MRI data and data adaptive dose finding studies in clinical trials. The classification of effusion synovitis (ES) in knee MRI data is a challenging problem due to the inherent nature of the data, where only a small percentage of the image is indicative of ES. As a result, the usage of popular image analysis algorithms produces poor classification performance in both the single and multi-slice case. Our work introduces a graph convolutional network (GCN) model to combine information both within and between-slice for MRI series to accurately classify ES. We first develop what we term the ‘single-slice’ model, where image networks are constructed from only one slice per MRI series and are used as input to our GCN. Our method outperforms commonly used existing models, with an area under the curve of 80.95 percent, and a Matthews correlation coefficient of 60.8. Next, we extend our method by constructing image networks across slices within an MRI series, which we term the ‘multi-slice’ model, allowing our method to reflect clinical practice. This approach increases classification performance and outperforms existing methods by a larger margin, with an area under the curve of 86.11 and a Matthews correlation coefficient of 57.5. Lastly, we turn our attention to dose finding in a phase 2 group sequential trial. We introduce the usage of a group-specific semi-parametric model that is formulated to select the model which minimizes prediction error given all observed data and assign doses to incoming groups. We show that our method results in a lower overall error for different types of phase 2 data when compared to the fully parametric and fully non-parametric model alone.Release after 01/21/202
Ideal Theory
No full textThe puzzle of how children are able to acquire linguistic structures and principles with seemingly little to no input to guide them – the “poverty of the stimulus” – has long motivated research in linguistics, particularly in generative syntax, where it has shaped the search for innate principles of grammar. I propose that the poverty of the stimulus is not an empirical generalization, but an artifact of model choice: the stimulus can be “enriched” simply by using a formalism that accounts for the interactions between the subsymbolic structures underlying symbolic language use. In this dissertation, I develop such a formalism using ideals, collections of subsymbolic cognitive patterns reflecting the range of variation in the cognitive representation for some concept, as the basic structural element. By exploiting the combinatorial properties of ideals, agents of a model gain access to vast stores of indirect positive evidence in the input that they can use to overcome the poverty of the stimulus. To show how, I build models of anaphoric one, Principle C, and the interaction between wh-movement and the complex noun phrase island constraint, all commonly considered evidence of an impoverished stimulus. In each case, agents can use ideals to construct linguistic representations that reflect the observed behavior by relying only on evidence freely available in the input. These examples demonstrate a set of strategies for solving poverty of the stimulus puzzles in general – without the need for innate grammatical principles
2024-2025 Growth, Physiology, Yield, and Quality Evaluation of Small Grain Varieties in Central Arizona
Get PDFChoosing an appropriate crop variety is critical for farmers, especially in Arizona’s small-grain production systems. There exists considerable variation among small grain varieties, with each displaying distinct levels of adaptability and performance traits that ultimately affect the profitability of farming ventures. The performance of varieties can fluctuate significantly from year to year, highlighting the importance of conducting evaluations across multiple site-years to assess a variety's yield potential accurately.Financial support for this project was received from the Arizona Grain Research and Promotion Council and the Arizona Crop Improvement Association